Business activity monitoring for logistics management systems

Abstract

Enterprises use different software for different purposes, such as accounting management, customer relationships, so that information technologies become an integral part of business processes. A business process turns out to be a combination of these different software, besides the received information/data by one of software tools that comes from another one. Different software systems cannot have been aware of each other directly. When the domain under consideration is container logistics, in addition to the different software, there are many relationships with other companies and so there are many different systems, variable types and file types that are being used. There are different transportation modes like highway, marine or airway, and by the expansion of intermodal transportation, tracking data is getting harder. For container logistics being a complicated business, tracking data is a necessity. The necessity is to track and to control the data that comes from outer systems and inner systems to an interoperable platform. This necessity enables trackable business processes and thus increases the business performance. In the scope of this thesis, a business activity monitoring environment is created in case of ARKAS Holding, which works on container logistics domain and Bimar Inc., which is the software provider of it. As it was mentioned above, this tracking needs cause to creation of the proposed and implemented monitoring environment for such a case of ARKAS Holding that does intermodal transportation, which has many endpoints in its business processes and there are too many data to be tracked. There are many different endpoints, such as marine, roadway and depot, in container logistics; also there are many different data types that are coming from different systems. Thus, the ‘Business Activity Monitoring’ environment is created as this thesis’ subject to make these different systems talk to each other, also to enable gathering data directly and automatically to achieve real-time monitoring.